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Coevolving Strategies for General Game Playing (2007)
Joseph Reisinger
,
Erkin Bahceci
,
Igor Karpov
and
Risto Miikkulainen
The General Game Playing Competition poses a unique challenge for Artificial Intelligence. To be successful, a player must learn to play well in a limited number of example games encoded in first-order logic and then generalize its game play to previously unseen games with entirely different rules. Because good opponents are usually not available, learning algorithms must come up with plausible opponent strategies in order to benchmark performance. One approach to simultaneously learning all player strategies is coevolution. This paper presents a coevolutionary approach using NeuroEvolution of Augmenting Topologies to evolve populations of game state evaluators. This approach is tested on a sample of games from the General Game Playing Competition and shown to be effective: It allows the algorithm designer to minimize the amount of domain knowledge built into the system, which leads to more general game play and allows modeling opponent strategies efficiently. Furthermore, the General Game Playing domain proves to be a powerful tool for developing and testing coevolutionary methods.
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PDF
Citation:
In
Proceedings of the {IEEE} Symposium on Computational Intelligence and Games
, 320-327, Piscataway, NJ, 2007. IEEE.
Bibtex:
@InProceedings{reisinger:cig07, title={Coevolving Strategies for General Game Playing}, author={Joseph Reisinger and Erkin Bahceci and Igor Karpov and Risto Miikkulainen}, booktitle={Proceedings of the {IEEE} Symposium on Computational Intelligence and Games}, address={Piscataway, NJ}, publisher={IEEE}, pages={320-327}, url="http://nn.cs.utexas.edu/?reisinger:cig07", year={2007} }
People
Erkin Bahceci
Ph.D. Alumni
erkin [at] cs utexas edu
Igor V. Karpov
Masters Alumni
ikarpov [at] gmail com
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Joseph Reisinger
Former Ph.D. Student
joeraii [at] cs utexas edu
Projects
NEAT: Evolving Increasingly Complex Neural Network Topologies
2000 - 2011
Areas of Interest
Evolutionary Computation
Neuroevolution
Game Playing